INFEWS/T1: A Modeling Framework to Understand the coupling of Food, Energy, and Water in the Teleconnected Corn and Cotton Belts

INFEWS/T1：了解远程连接的玉米和棉花带中食品、能源和水耦合的建模框架

• 批准号: 1639327
• 负责人: Xin-Zhong Liang
• 金额: $ 300万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1639327&HistoricalAwards=false
• 关键词: INFEWS; T1; Modeling; Framework; Understand

The resilience of U.S. agriculture is significantly impacted by increasing climate extremes, growing population demands, and evolving land use. This project will develop, evaluate, and apply a model of the coupled Food, Energy, and Water (FEW) systems across the Corn and Cotton Belts of the Midwest, Southeast and Great Plains. The study will evaluate food crops currently grown in these Belts as well as the potential for growing bioenergy crops on marginal land. The project will: (1) develop a FEW model framework that represents the coupled nature of food and bioenergy production and water and its responses to environmental forcings and human interventions; (2) enhance understanding of key feedback mechanisms within FEW systems; (3) determine potential thresholds in FEW systems that would indicate damage to the resilience of U.S. agriculture and water resources. The project will provide training for PhD students and postdoctoral researchers in transdisciplinary research where cross-fertilization of ideas is central. Building upon existing partnerships with Minority-Serving Institutions, the project will also involve minority students through summer internships. This project will integrate state-of-the-art knowledge and modeling across the climate, hydrologic, agronomic, biogeochemical, engineering, and economic sciences. The project will use this integrated model to evaluate the coupled nature of food and bioenergy production, water quantity and quality, and climate and hydrologic processes in response to environmental forcings and human interventions. This activity will advance the transdisciplinary science by building diverse systems knowledge to address critical issues of vulnerability, resilience and sustainability. Specifically, the project will develop a scale-dependent approach for coupling, predicting and applying the interactive water, carbon, and nitrogen cycle processes with agriculture, water resources, the biofuels industry and economic practices. This will enable the larger-scale impacts of external forcings (e.g., increasing climate extremes and population demands) to be directly coupled to the impacts of human interventions (e.g., infrastructure and management) and decision level information. It will improve the scientific basis for decisions in sustainable agricultural food and bioenergy practices, water resources management and pollution assessment, hydroengineering design, and adaptation and mitigation strategies.

美国农业的复原力受到极端气候加剧、人口需求增长和土地利用不断变化的重大影响。该项目将开发、评估和应用中西部、东南部和大平原玉米和棉花带的粮食、能源和水（FEW）耦合系统模型。该研究将评估目前在这些地带种植的粮食作物以及在边际土地上种植生物能源作物的潜力。该项目将：（1）开发一个FEW模型框架，该框架代表粮食和生物能源生产与水的耦合性质及其对环境强迫和人类干预的响应;（2）加强对FEW系统中关键反馈机制的理解;（3）确定FEW系统中可能的阈值，这些阈值表明美国农业和水资源的恢复力受到损害。 该项目将为博士生和博士后研究人员提供跨学科研究方面的培训，其中思想交流是核心。在与少数群体服务机构现有伙伴关系的基础上，该项目还将通过暑期实习让少数群体学生参与。该项目将整合气候、水文、农学、地球化学、工程和经济科学的最先进的知识和建模。该项目将使用这一综合模型来评估粮食和生物能源生产、水量和水质以及气候和水文过程对环境强迫和人类干预的响应的耦合性质。这项活动将通过建立不同的系统知识来促进跨学科科学，以解决脆弱性，复原力和可持续性等关键问题。具体而言，该项目将开发一种依赖规模的方法，用于耦合、预测和应用与农业、水资源、生物燃料工业和经济实践相互作用的水、碳和氮循环过程。 这将使更大规模的外部强迫的影响（例如，日益增加的极端气候和人口需求）与人类干预的影响直接相关（例如，基础设施和管理）和决策级信息。它将改善可持续农业粮食和生物能源做法、水资源管理和污染评估、水利工程设计以及适应和减缓战略方面的决策的科学基础。

项目成果

Understanding and Reducing Warm and Dry Summer Biases in the Central United States: Analytical Modeling to Identify the Mechanisms for CMIP Ensemble Error Spread

了解并减少美国中部温暖干燥的夏季偏差：通过分析模型确定 CMIP 集合误差传播机制

• DOI: 10.1175/jcli-d-22-0255.1
• 发表时间: 2023
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Sun, Chao;Liang, Xin-Zhong
• 通讯作者: Liang, Xin-Zhong

CWRF performance at downscaling China climate characteristics

• DOI: 10.1007/s00382-018-4257-5
• 发表时间: 2019-02
• 期刊: Climate Dynamics
• 影响因子: 4.6
• 作者: Xin‐Zhong Liang;Chao Sun;Xiaohui Zheng;Yongjiu Dai;Min Xu;H. Choi;Tiejun Ling;F. Qiao;X. Kong-X

Climate change will pose challenges to water quality management in the st. Croix River basin

气候变化将对圣路易斯的水质管理带来挑战。

• DOI: 10.1016/j.envpol.2019.04.129
• 发表时间: 2019
• 期刊: Environmental Pollution
• 影响因子: 8.9
• 作者: Yang, Qichun;Zhang, Xuesong;Almendinger, James E.;Huang, Maoyi;Chen, Xingyuan;Leng, Guoyong;Zhou, Yuyu;Zhao, Kaiguang;Asrar, Ghassem R.;Li, Xia
• 通讯作者: Li, Xia

Model Use in WEF Nexus Analysis: a Review of Issues

WEF Nexus 分析中的模型使用：问题回顾

• DOI: 10.1007/s40518-017-0078-0
• 发表时间: 2017
• 期刊: Current Sustainable/Renewable Energy Reports
• 作者: McCarl, Bruce A.;Yang, Yingqian;Schwabe, Kurt;Engel, Bernard A.;Mondal, Alam Hossain;Ringler, Claudia;Pistikopoulos, Efstratios N.
• 通讯作者: Pistikopoulos, Efstratios N.

Developing the Coupled CWRF‐FVCOM Modeling System to Understand and Predict Atmosphere‐Watershed Interactions Over the Great Lakes Region

• DOI: 10.1029/2020ms002319
• 发表时间: 2020-11
• 期刊: Journal of Advances in Modeling Earth Systems
• 影响因子: 6.8
• 作者: Lei Sun;Xin‐Zhong Liang;Meng Xia